Mapping of the Wnt/β-Catenin/TCF Response Elements in the Human Versican Promoter
Bibliographic record
Abstract
Versican, a chondroitin sulfate proteoglycan, is one of the main components of the extracellular matrix and is considered to be crucial to several key cellular processes involved in development and disease. There is differential temporal and spatial expression of versican by multiple cell types and in different developmental and pathological timeframes. In order to fully appreciate the functional roles of versican as it relates to changing patterns of expression in development and disease, an in-depth knowledge of versican's biosynthetic processing is necessary. We have recently shown that β-catenin/T-cell factor (TCF) complex formation at the versican promoter site is essential for activation of versican transcription. The transcriptional activator β-catenin is the key mediator of the canonical Wnt signaling pathway. However, β-catenin does not itself bind DNA and thus functions via interaction with TCF/Lymphoid-enhancing factor (LEF) transcription factors. These proteins contain a high-mobility group (HMG) box that binds DNA in a sequence-specific manner. Thus, in the case of active Wnt signaling, β-catenin activates, in cooperation with proteins of the TCF/LEF family, the expression of a wide variety of target genes. The goal of this chapter is to describe the techniques used to elucidate the transcriptional control of versican by the β-catenin/TCF response elements in its promoter site and to demonstrate how this signaling may be assayed experimentally. These approaches provide insight into the transcriptional regulation of the versican gene and provide the basis for the identification of novel Wnt/β-catenin/TCF-regulated genes that are part of the signaling machinery regulating early embryogenesis, neoplasia, and cardiovascular remodeling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".